2 papers
cs.LG2022
XOOD: Extreme Value Based Out-Of-Distribution Detection For Image Classification
Frej Berglind, Haron Temam, Supratik Mukhopadhyay +4
Detecting out-of-distribution (OOD) data at inference time is crucial for many applications of machine learning. We present XOOD: a novel extreme value-based OOD detection framewor…
cs.DC2018
CADDeLaG: Framework for distributed anomaly detection in large dense graph sequences
Aniruddha Basak, Kamalika Das, Ole J. Mengshoel
Random walk based distance measures for graphs such as commute-time distance are useful in a variety of graph algorithms, such as clustering, anomaly detection, and creating low di…